Giovanni De Toni
Research Scientist - Mobile and Social Computing Lab
Human-centric and Responsible AI
Fondazione Bruno Kessler (FBK)

Hi 👋! I am Giovanni and I am a Research Scientist at Fondazione Bruno Kessler (FBK). My research focuses on the algorithmic challenges involved in ensuring human oversight of AI systems and understanding their effects when deployed in social contexts.

I hold a PhD from the University of Trento (cum laude), advised by Bruno Lepri and Andrea Passerini. I was also part of the European Laboratory for Learning and Intelligent Systems (ELLIS) PhD network, through which I spent some time at the Max Planck Institute for Software Systems working with Manuel Gomez Rodriguez. Throughout my academic journey, I conducted research as a visiting scientist or intern at several institutions, including the European Commission, Google X, and CERN. Before my PhD, I was a Research Scientist at VUI, Inc., a Boston-based startup (now acquired) developing innovative conversational AI technologies. In the past, I have also contributed to several open-source scientific libraries (e.g., Shogun).


Latest News

Publications & Preprints

  1. Multiclass Local Calibration With the Jensen-Shannon Distance
    Cesare Barbera, Lorenzo Perini, Giovanni De Toni,, Andrea Passerini, Andrea Pugnana
    Preprint
    [paper][code]

  2. To Ask or Not to Ask: Learning to Require Human Feedback
    Andrea Pugnana*, Giovanni De Toni*, Cesare Barbera*, Roberto Pellungrini, Bruno Lepri, Andrea Passerini
    Preprint (* equal contribution)
    [paper][code]

  3. Revisiting (Un)Fairness in Recourse by Minimizing Worst-Case Social Burden
    Ainhize Barrainkua, Giovanni De Toni, Jose Antonio Lozano, Novi Quadrianto
    to appear in AAAI 2026
    Oral
    [paper][code]

  4. 🏆 You Don’t Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control
    Giovanni De Toni, Erasmo Purificato, Emilia Gomez, Andrea Passerini, Bruno Lepri, Cristian Consonni
    RecSys: 19th ACM Conference on Recommender Systems (2025)
    Best Full Paper Award at 19th ACM Conference on Recommender Systems (ACM RecSys 2025)
    [paper][code]

  5. Time Can Invalidate Algorithmic Recourse
    Giovanni De Toni, Stefano Testo, Bruno Lepri, Andrea Passerini
    FAccT: ACM Conference on Fairness, Accountability, and Transparency (2025)
    [paper][code]

  6. Towards Human-AI Complementarity with Predictions Sets
    Giovanni De Toni, Nastaran Okati, Suhas Thejaswi, Eleni Straitouri, Manuel Gomez-Rodriguez
    NeurIPS (2024)
    [paper][code]

  7. 🏆 Preference Elicitation in Interactive and User-centered Algorithmic Recourse: an Initial Exploration
    Seyedehdelaram Esfahani, Giovanni De Toni, Bruno Lepri, Andrea Passerini, Katya Tentori, Massimo Zancanaro
    ACM UMAP (2024)
    Best Short Paper Runner-up at the 32nd ACM UMAP Conference (2024)
    [paper][code]

  8. Personalized Algorithmic Recourse with Preference Elicitation
    Giovanni De Toni, Paolo Viappiani, Stefano Teso, Bruno Lepri, Andrea Passerini
    Transactions on Machine Learning Research (2024)
    [paper][code]

  9. Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis
    Giovanni De Toni, Bruno Lepri, Andrea Passerini
    Machine Learning (2023)
    [paper][code]